Reliability-based robust design optimization of gap size of annular nuclear fuels using kriging and inverse distance weighting methods

Jaehyeok Doh, Younghoon Kim, Jongsoo Lee

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

In this study, the design optimization of the gap size of annular nuclear fuels used in pressurized water reactors (PWRs) was performed. For this, thermoelastic–plasticity–creep (TEPC) analysis of PWR annular fuels was carried out using an in-house code to investigate the performance of nuclear fuels. Surrogate models based on the kriging and inverse distance weighting models were generated using computational performance data based on optimal Latin hypercube design. Using these surrogate models, the gap size of PWR annular fuel was deterministically optimized using the micro-genetic algorithm to improve the heat transfer efficiency and maintain a lower level of stress. Reliability-based design optimization and reliability-based robust design optimization were conducted to satisfy target reliability and secure the robustness of the PWRs’ performance. The optimal gap size was validated through TEPC analysis and the optimum solutions were compared according to the approximate method and reliability index.

Original languageEnglish
Pages (from-to)2161-2176
Number of pages16
JournalEngineering Optimization
Volume50
Issue number12
DOIs
Publication statusPublished - 2018 Dec 2

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Management Science and Operations Research
  • Control and Optimization
  • Industrial and Manufacturing Engineering
  • Applied Mathematics

Cite this